Company description Manager, Data Engineering Company Description Publicis Sapient is a digital transformation partner helping established organizations get to their future, digitally-enabled state, both in the way they work and the way they serve their customers. We help unlock value through a start-up mindset and modern methods, fusing strategy, consulting and customer experience with agile engineering and problem-solving creativity. United by our core values and our purpose of helping people thrive in the brave pursuit of next, our 20,000+ people in 53 offices around the world combine experience across technology, data sciences, consulting, and customer obsession to accelerate our clients s businesses through designing the products and services their customers truly value. Overview As a Manager, Data Engineering at Publicis Sapient, you will guide clients through complex data challenges, architecting and implementing innovative solutions that drive digital transformation. Your role will be focused on delivering high-quality solutions by independently driving design discussions related to Data Ingestion, Transformation & Consumption, Data Storage and Computation Frameworks, Performance Optimizations, Infrastructure, Automation & Cloud Computing, and Data Governance & Security. The role requires a hands-on technologist with expertise in Big Data solution architecture and with a strong programming background in Java / Scala / Python. You will work closely with clients across industries, helping them navigate their digital transformation journeys by delivering scalable, high-quality data solutions. Responsibilities Your Impact: Provide technical leadership and hands-on implementation role in the areas of data engineering including data ingestion, data access, modeling, data processing, visualization, design, and implementation. Lead a team to deliver high quality big data technologies-based solutions on Azure Cloud. Manage functional & nonfunctional scope and quality. Help establish standard data practices like governance and address other non-functional issues like data security, privacy, and quality. Manage and provide technical leadership to a data program implementation based on the requirement using agile technologies. Participate in workshops with clients and align client stakeholders to optimal solutions. Consulting, Soft Skills, Thought Leadership, Mentorship etc. People management, contributing to hiring and capability building. Qualifications Your Skills & Experience: Overall 8+ years of IT experience with 3+ years in Data related technologies, and expertise of 1+ years in data-related Azure Cloud services and delivered at least 1 project as an architect. Mandatory to have knowledge of Big Data Architecture Patterns and experience in the delivery of end-to-end Big Data solutions on Cloud (Azure/AWS/GCP) Expert in programming languages like Java/ Scala and good to have Python Expert in at least one distributed data processing framework: Spark (Core, Streaming, SQL), Storm or Flink, etc. Expert in Hadoop eco-system with Azure cloud distribution and worked at least on one or more big data ingestion tools (Sqoop, Flume, NiFI, etc), distributed messaging and ingestion frameworks (Kafka, Pulsar, Pub/Sub, etc) and good to know traditional tools like Informatica, Talend, etc Should have worked on any NoSQL solutions like Mongo DB, Cassandra, HBase, etc, or Cloud-based NoSQL offerings like DynamoDB, Big Table, etc. Good Exposure in development with CI / CD pipelines. Knowledge of containerization, orchestration, and Kubernetes engine would be an added advantage. Experience with Informatica (nice to have). Basic knowledge of Gen AI (good to have). Additional information Set Yourself Apart With: Certification on GCP/AWS any cloud platform or big data technologies. Strong analytical and problem-solving skills. Excellent understanding of data technologies landscape/ecosystem Experience or exposure to ML/AI engineering Experience with containerization and associated microservice tooling such as Docker, and Kubernetes. Knowledge of data security (authentication, authorization, encryption for data at rest and in transit). Understanding of monitoring and alerting tools for data environments. Exposure to data governance, cataloging, and lineage tools. Cloud or data technology certifications. Active participation in the Data Engineering community (blogs, keynotes, POCs, hackathons). Experience or exposure to working with Software or Platform engineering teams A Bachelor s or Master’s degree in Computer Engineering, Computer Science, or a related field.